Ontology for Intelligent Disease Diagnosis

This research develops a comprehensive ontology to improve intelligent disease diagnosis by addressing gaps in current medical ontologies. By systematically organizing and analyzing medical data, the ontology enhances diagnostic accuracy and efficiency. The methodology includes a literature study and the development of an ontology-based on key concepts and relationships in the health domain. Results indicate that a more complete ontology supports better clinical decisions. Despite challenges in data collection and validation, the study contributes to improved medical care quality. Future research should focus on integrating machine learning and AI to enhance reasoning and prediction capabilities